
import pandas as pd
import plotly.express as px
import plotly.io as pio
from dateutil import parser
from dateutil.relativedelta import *


covidData = pd.read_csv("owid_covid-19-data_latest_covid-19-world-cases-deaths-testing.csv")
covidData = covidData[['iso_code','continent','location','total_cases','total_deaths','new_cases', 'new_deaths','life_expectancy','median_age','date']]


covidData = covidData.bfill() #Next Observation Carried Backward
display(covidData)


fig=px.line(covidData,x = 'date',
y='new_deaths',color='continent',
title='New covid deaths of each continent')
fig.show()


fig=px.line(covidData,x = 'date',
y='new_cases',color='continent',
title='New covid cases of each continent')
fig.show()


fig=px.pie(covidData,values='total_cases',names='continent',title='Total cases based on continet')
fig.show()


fig=px.pie(covidData,values='total_deaths',names='continent',title='Total deaths based on  continet')
fig.show()


country_info = covidData[covidData['location']=='India']
fig=px.line(country_info,x ='date',
y='new_cases',
title='New covid cases of India')
fig.show()


country_info = covidData[covidData['location']=='United States']
fig=px.line(country_info,x ='date',
y='new_cases',
title='New covid cases of United States')
fig.show()

	iso_code	continent	location	total_cases	total_deaths	new_cases	new_deaths	life_expectancy	median_age	date
0	AFG	Asia	Afghanistan	5.0	1.0	5.0	1.0	64.83	18.6	2020-02-24
1	AFG	Asia	Afghanistan	5.0	1.0	0.0	1.0	64.83	18.6	2020-02-25
2	AFG	Asia	Afghanistan	5.0	1.0	0.0	1.0	64.83	18.6	2020-02-26
3	AFG	Asia	Afghanistan	5.0	1.0	0.0	1.0	64.83	18.6	2020-02-27
4	AFG	Asia	Afghanistan	5.0	1.0	0.0	1.0	64.83	18.6	2020-02-28
...	...	...	...	...	...	...	...	...	...	...
201494	ZWE	Africa	Zimbabwe	255953.0	5565.0	14.0	1.0	61.49	19.6	2022-07-11
201495	ZWE	Africa	Zimbabwe	255981.0	5565.0	28.0	0.0	61.49	19.6	2022-07-12
201496	ZWE	Africa	Zimbabwe	255981.0	5565.0	0.0	0.0	61.49	19.6	2022-07-13
201497	ZWE	Africa	Zimbabwe	256047.0	5566.0	66.0	1.0	61.49	19.6	2022-07-14
201498	ZWE	Africa	Zimbabwe	256083.0	5566.0	36.0	0.0	61.49	19.6	2022-07-15